OPEN-SOURCE SCRIPT
Indicator: Profitability by Day & Hour (stacked, non-overlay)
What it does
This tool performs a simple seasonality study on the selected symbol. It measures historical returns and summarizes them in two horizontal heatmaps:
Hours table (top) — Columns 00–23 show the average return of each clock hour, plus sample size, win rate, volatility (SD), and a t-score.
Days table (middle) — Columns 1–7 correspond to Mon–Sun with the same metrics.
Summary (bottom) — Shows the most profitable day and hour in the history loaded on your chart.
Green cells indicate higher average returns; red cells indicate lower/negative averages. The layout is centered on the screen, with the hours table above the days table for quick scanning.
How it works (methodology)
Returns: by default the indicator uses log returns ln(Ct/Ct-1) (you can switch to simple % if you prefer).
Daily aggregation (no look-ahead): day statistics are computed from completed daily closes via a higher timeframe request. Yesterday’s daily close vs. the prior day is added to the appropriate weekday bucket, preventing repaint/forward bias.
Hourly aggregation (intraday only): hour statistics are computed bar-to-bar on the current intraday timeframe and accumulated by clock hour (00–23) of the symbol’s exchange timezone.
Metrics per bucket:
Mean: average return in that bucket.
n: number of observations.
Win%: share of positive returns.
SD: standard deviation of returns (volatility proxy).
t-score: mean / SD * sqrt(n) — a quick stability signal (not a hypothesis test).
The indicator does not rely on future data and does not repaint past values.
Reading the tables
Start with the Mean row in each table: it’s color-mapped (red → yellow → green).
Check n (sample size). A bright green cell with very low n is less meaningful than a mild green cell with large n.
Use Win% and SD to judge consistency and noise.
t-score is a compact “signal-to-noise × sample size” measure; higher absolute values suggest more stable effects.
Typical observations traders look for (purely illustrative): for some equity indices, the first hour after the cash open can dominate; for FX/crypto, certain late-US or early-Asia hours sometimes stand out. Always verify on your symbol and timeframe.
This tool performs a simple seasonality study on the selected symbol. It measures historical returns and summarizes them in two horizontal heatmaps:
Hours table (top) — Columns 00–23 show the average return of each clock hour, plus sample size, win rate, volatility (SD), and a t-score.
Days table (middle) — Columns 1–7 correspond to Mon–Sun with the same metrics.
Summary (bottom) — Shows the most profitable day and hour in the history loaded on your chart.
Green cells indicate higher average returns; red cells indicate lower/negative averages. The layout is centered on the screen, with the hours table above the days table for quick scanning.
How it works (methodology)
Returns: by default the indicator uses log returns ln(Ct/Ct-1) (you can switch to simple % if you prefer).
Daily aggregation (no look-ahead): day statistics are computed from completed daily closes via a higher timeframe request. Yesterday’s daily close vs. the prior day is added to the appropriate weekday bucket, preventing repaint/forward bias.
Hourly aggregation (intraday only): hour statistics are computed bar-to-bar on the current intraday timeframe and accumulated by clock hour (00–23) of the symbol’s exchange timezone.
Metrics per bucket:
Mean: average return in that bucket.
n: number of observations.
Win%: share of positive returns.
SD: standard deviation of returns (volatility proxy).
t-score: mean / SD * sqrt(n) — a quick stability signal (not a hypothesis test).
The indicator does not rely on future data and does not repaint past values.
Reading the tables
Start with the Mean row in each table: it’s color-mapped (red → yellow → green).
Check n (sample size). A bright green cell with very low n is less meaningful than a mild green cell with large n.
Use Win% and SD to judge consistency and noise.
t-score is a compact “signal-to-noise × sample size” measure; higher absolute values suggest more stable effects.
Typical observations traders look for (purely illustrative): for some equity indices, the first hour after the cash open can dominate; for FX/crypto, certain late-US or early-Asia hours sometimes stand out. Always verify on your symbol and timeframe.
オープンソーススクリプト
TradingViewの精神に則り、この作者はスクリプトのソースコードを公開しているので、その内容を理解し検証することができます。作者に感謝です！無料でお使いいただけますが、このコードを投稿に再利用する際にはハウスルールに従うものとします。
免責事項
これらの情報および投稿は、TradingViewが提供または保証する金融、投資、取引、またはその他の種類のアドバイスや推奨を意図したものではなく、またそのようなものでもありません。詳しくは利用規約をご覧ください。
オープンソーススクリプト
TradingViewの精神に則り、この作者はスクリプトのソースコードを公開しているので、その内容を理解し検証することができます。作者に感謝です！無料でお使いいただけますが、このコードを投稿に再利用する際にはハウスルールに従うものとします。
免責事項
これらの情報および投稿は、TradingViewが提供または保証する金融、投資、取引、またはその他の種類のアドバイスや推奨を意図したものではなく、またそのようなものでもありません。詳しくは利用規約をご覧ください。